# -*- coding:utf-8 -*-

import tensorflow as tf
import numpy as np

x_data=np.float32(np.random.rand(2,100))
y_data=np.dot([0.100,0.200],x_data)+0.300

b=tf.Variable(tf.zeros([1]))
w=tf.Variable(tf.random_uniform([1,2],-1.0,1.0))
y=tf.matmul(w,x_data)+b

loss=tf.reduce_mean(tf.square(y-y_data))
optimizer=tf.train.GradientDescentOptimizer(0.5)
train=optimizer.minimize(loss)

init=tf.initialize_all_variables()

sess=tf.Session()
sess.run(init)

for step in range(0,201):
    sess.run(train)
    if step % 10==0:
        print(step,sess.run(w),sess.run(b))
